Hydraulic parameter estimation and 3D facies modeling of the Nubian aquifer in Siwa Oasis, Egypt: Integrating self-organizing maps, Kozeny-Carmen, and pumping tests

Siwa Oasis in Egypt faces critical water management challenges due to its arid climate, complete dependence on groundwater, and rapid aquifer salinization. The Oasis relies entirely on two main aquifers, the shallow Tertiary Carbonate Aquifer (TCA) and the deep Nubian Sandstone Aquifer System (NSAS) with no significant recharge due to minimal rainfall and extreme evaporation rates. This study integrates Self-Organizing Maps (SOM), k-means clustering, and hydrogeological methods to characterize the NSAS and estimate critical hydraulic parameters. Geophysical well logs were analyzed using unsupervised machine learning techniques to delineate aquifer layers and construct a novel 3D facies model. The Kozeny-Carman equation was applied for hydraulic conductivity estimation and validated against pumping test data. SOM clustering identified distinct lithological units and depositional environments, while 3D modeling mapped subsurface heterogeneity across porosity, shale volume, and hydraulic conductivity distributions. Results reveal hydraulic conductivity ranging from 1.2 to 6.6 m/d, effective porosity between 24 % and 40 %, and shale volume from 0 % to 60 % across the NSAS. The central and eastern parts of Siwa Oasis emerge as optimal zones for sustainable groundwater extraction. High-porosity channel sands were identified as primary aquifer units, while finer-grained floodplain deposits act as flow barriers. This represents the first systematic application of machine learning for aquifer characterization in Siwa Oasis, providing essential data for sustainable groundwater management and future drilling. • SOM and k-means successfully delineated lithological units in Siwa aquifer. • Hydraulic parameters estimated using Kozeny-Carman and pumping tests. • 3D facies model reveals high-porosity zones for groundwater management. • Sand layers shift upward east-to-west due to tectonic activity. • Central and eastern Siwa identified as optimal groundwater extraction zones.

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Publication Details

Journal
Journal of Hydrology Regional Studies
Published
2025-11-08
DOI
https://doi.org/10.1016/j.ejrh.2025.102915
Primary Topic
Groundwater flow and contamination studies
Type
article
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article

Hydraulic parameter estimation and 3D facies modeling of the Nubian aquifer in Siwa Oasis, Egypt: Integrating self-organizing maps, Kozeny-Carmen, and pumping tests

Mohamed Hamdy Eid, Hatem Saad Ramadan, Attila Kovács, Mostafa R. Abukhadra et al.
Journal of Hydrology Regional Studies
Groundwater flow and contamination studies
article

Hydraulic parameter estimation and 3D facies modeling of the Nubian aquifer in Siwa Oasis, Egypt: Integrating self-organizing maps, Kozeny-Carmen, and pumping tests

Mohamed Hamdy Eid, Hatem Saad Ramadan, Attila Kovács, Mostafa R. Abukhadra, Ahmed S. Elshall, Haifa A. Alqhtani, Mohamed Ayed Elbalawy, Saleh Dabaa, Péter Szűcs
article en

Abstract

Siwa Oasis in Egypt faces critical water management challenges due to its arid climate, complete dependence on groundwater, and rapid aquifer salinization. The Oasis relies entirely on two main aquifers, the shallow Tertiary Carbonate Aquifer (TCA) and the deep Nubian Sandstone Aquifer System (NSAS) with no significant recharge due to minimal rainfall and extreme evaporation rates. This study integrates Self-Organizing Maps (SOM), k-means clustering, and hydrogeological methods to characterize the NSAS and estimate critical hydraulic parameters. Geophysical well logs were analyzed using unsupervised machine learning techniques to delineate aquifer layers and construct a novel 3D facies model. The Kozeny-Carman equation was applied for hydraulic conductivity estimation and validated against pumping test data. SOM clustering identified distinct lithological units and depositional environments, while 3D modeling mapped subsurface heterogeneity across porosity, shale volume, and hydraulic conductivity distributions. Results reveal hydraulic conductivity ranging from 1.2 to 6.6 m/d, effective porosity between 24 % and 40 %, and shale volume from 0 % to 60 % across the NSAS. The central and eastern parts of Siwa Oasis emerge as optimal zones for sustainable groundwater extraction. High-porosity channel sands were identified as primary aquifer units, while finer-grained floodplain deposits act as flow barriers. This represents the first systematic application of machine learning for aquifer characterization in Siwa Oasis, providing essential data for sustainable groundwater management and future drilling. • SOM and k-means successfully delineated lithological units in Siwa aquifer. • Hydraulic parameters estimated using Kozeny-Carman and pumping tests. • 3D facies model reveals high-porosity zones for groundwater management. • Sand layers shift upward east-to-west due to tectonic activity. • Central and eastern Siwa identified as optimal groundwater extraction zones.

Journal of Hydrology Regional StudiesVol. 62
Princess Nourah bint Abdulrahman University (SA), Ain Shams University (EG), Beni-Suef University (EG), Ministry of Water Resources and Irrigation (EG), United Arab Emirates University (AE), University of Miskolc (HU), Florida Gulf Coast University (US), National University of Water and Environmental Engineering (UA)
Openalex Percentile: Top 69%
Groundwater flow and contamination studies
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